Cytotoxicity and Cell Cycle Effects of Bare and Poly(vinyl alcohol)‐Coated Iron Oxide Nanoparticles in Mouse Fibroblasts
Bibliographic record
Abstract
Abstract Super‐paramagnetic iron oxide nanoparticles (SPIONs) are recognized as powerful biocompatible materials for use in various biomedical applications, such as drug delivery, magnetic‐resonance imaging, cell/protein separation, hyperthermia and transfection. This study investigates the impact of high concentrations of SPIONs on cytotoxicity and cell‐cycle effects. The interactions of surface‐saturated (via interactions with cell medium) bare SPIONs and those coated with poly(vinyl alcohol) (PVA) with adhesive mouse fibroblast cells (L929) are investigated using an MTT assay. The two SPION formulations are synthesized using a co‐precipitation method. The bare and coated magnetic nanoparticles with passivated surfaces both result in changes in cell morphology, possibly due to clustering through their magnetostatic effect. At concentrations ranging up to 80 × 10−3 M, cells exposed to the PVA‐coated nanoparticles demonstrate high cell viability without necrosis and apoptosis. In contrast, significant apoptosis is observed in cells exposed to bare SPIONs at a concentration of 80 × 10−3 M. Nanoparticle exposure (20–80 × 10−3 M) leads to variations in both apoptosis and cell cycle, possibly due to irreversible DNA damage and repair of oxidative DNA lesions, respectively. Additionally, the formation of vacuoles within the cells and granular cells indicates autophagy cell death rather than either apoptosis or necrosis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".